Tag Archives: Artificial Intelligence

Top ERP Trends to Watch in 2023

An ERP is the backbone of business operations. It helps with every function you can think of; Operations, Sales, Customer Support, Marketing, and internal supporting teams such as HR, Legal, and IT. If you’re using an ERP such as the one offered by NetSuite, even the Finance department can be integrated into a single environment.

The type of ERP a business uses is mainly determined by the size of the business, what industry the company operates in, and the future strategy and goals; is the business planning to grow further or is already at a specific sweet spot? However, there are certain functionalities that enterprises must focus on that are absolute for an effective ERP deployment. These include whether the ERP is cloud-based, whether it has a mobile application, what different teams the ERP can serve well, or how much integration an ERP can facilitate.

Often businesses deploy an ERP in segments, some core departments are onboarded first, and the rest follow. That can also impact the type of ERP a company chooses to use. Below we look at an ERP, its many benefits, and the top ERP trends to watch for in 2023. We highlight what is essential for businesses and the latest cutting-edge ERP product offering that various solutions providers are at the forefront of.

What is an ERP?

ERP, also known as Enterprise Resource Planning, has its root in supply chain management systems used by manufacturers called Materials Requirements Planning (MRP). MRPs are mainly used to plan around inventories efficiently and manage production based on supply and demand. Similarly, an ERP helps companies manage financial resources where businesses record transactions and accounting entries in the general ledger and oversee accounts receivables, payables, and payroll. An ERP also has a robust financial reporting functionality offering rich insight into specific operations and the overall health of a company.

The ERP Trends to Watch in 2023

The Cloud and Hybrid Deployment Model

With over 20 years of companies offering cloud-based services or ERP solutions, it’s hard to imagine that not all ERPs today aren’t cloud-based. Chief Technology Officers worldwide say that over 50% of all IT spending this year will be on cloud computing. So that means that some portion of the nearly 50% that isn’t cloud-related will go towards traditional IT spending, such as servers and on-premise data centers. These house on-premise software deployments, including ERPs.

There have been legitimate reasons for businesses not to shift to the cloud, including security, resiliency, and whether data storage on the cloud is hosted in another country.

However, on-premises ERPs carry their own set of risks. How much and for how long do security and Support exist or legacy operating systems running these ERP systems? Can they find staff to manage these systems easily, and do the costs of doing so outweigh the cost of migrating to the cloud?

In a nutshell, businesses are still in the midst of a transition to the cloud. However, the shift has accelerated. Work dynamics are changing as more employees work from home, making ERPs that aren’t on a cloud riskier and untenable.

That’s not to say that the on-premises deployment model will completely disappear. A hybrid approach still makes sense for many businesses. Resiliency is a big concern as service outages by cloud service providers, however brief, can wreak havoc on businesses.

Mobile

Mobile was once viewed as a tertiary feature that was more gimmicky than nice to have. Over time, it started to become a value add. Today, given the changes in how we work and the advancements in mobile devices such as tablets, mobile is becoming the de-facto standard. As employees work from anywhere and work shifts to the cloud, a mobile iteration of an ERP is an absolute must from any service provider.

The mobile version of an ERP offers tremendous productivity by allowing customers to access it from anywhere at any time. Second, besides the user interface, the underlying technology isn’t that different from the regular version of the ERP since they’re both cloud-based.

Furthermore, a mobile ERP may be better than a traditional ERP as it allows customers to quickly capture and upload receipts or other transactions that need to be recorded in real-time. This goes beyond productivity and more into the realm of user adoption and compliance with timely expense report filings.

Finally, we’re all well aware of one of the best benefits of ERP, enhanced decision-making based on all the data gathered and easily and intuitively presented. As customers are further inclined to adopt the usage of an ERP motivated by the real-time benefits of mobile functionality, businesses will also see improvements based on quicker data capture and resulting analytics and reporting.

Artificial Intelligence

No product escapes the mention of Artificial Intelligence (AI) or similar terms such as Machine Learning (ML), Robotic Process Automation (RPA, and the like. And an ERP is no exception. No, AI won’t be taking over human tasks entirely in 2023, but it is viewed as a tool to drive productivity by automating the more mundane and repetitive tasks of customers.

Recurring deprecation expenses for assets can be recorded automatically based on their specific duration. Transactions can be automatically recorded in the applicable expense accounts based on precedents. Also, the ERP can execute relevant alerts and reminders for tasks such as asset revaluations, and receivables follow-ups, among others.

Furthermore, as more businesses use a subscription-based revenue model, they can automatically send periodic invoices for that subscription fee, record the transaction and process the payment without human interaction.

Increasingly, AI is used to identify internal audit red flags, client credit risks, and product sales recommendations based on customer personas and use cases. We predict that ERPs will leverage AI to streamline the customer experience further. Upon closing a sale, AI will allow businesses to generate invoices, onboard customers autonomously, and even recommend renewal price increases based on relevant factors.

The adoption of AI in ERP offers unprecedented efficiency by delivering automation, interactive advisory-type reviews, eliminating mundane and repetitive tasks, and reducing mistakes.

A blurring of the lines between ERP and CRM

In a way, you can call it the flywheel effect. Businesses have been successful with ERPs and CRM, Customer Relationship Management, software for over two decades. CRM was the first cloud-based business targeting companies with a new way of connecting and collaborating internally and introducing an entirely new paradigm on the customer experience.

Salesforce.com improved how companies supported, marketed, sold to, and conducted email campaigns outreaches to customers. The use of CRMs allowed all these functions to leverage data by setting up a single repository of all forms of interactions with existing and potential customers.

The data allowed companies to recalibrate messaging in a very targeted manner. Today, there isn’t only a sales or marketing team or a customer service team. Now, we have an exact science devised around the client: Customer Experience. As businesses captured the best practices for marketing to customers, sales processes, onboarding, and continuous hand-holding after the close via Support, they decided to codify these processes into an entirely new business practice, known as the customer lifecycle. Today, Sales, Support, Customer Success, and Account Management teams are all integrated and easily able to collaborate with one another.

Will all the intelligence available from a CRM, it is surprising that such systems are still a world apart from the ERPs used at firms. Shouldn’t the high-touch nature of a client, as evidenced by the CRM, factor into the contribution margins? Can the ERP calculating those margins easily capture that data for a CRM?

Companies like NetSuite have started offering unified solutions for both CRM and ERP. It is the logical next step to leverage the combined data sets of both systems. With an integrated offering, businesses can target customers based on specific financial benchmarks. Although businesses may already be able to see the total contract values of their customers or have a good gauge on the customer’s lifetime value. However, can companies easily calculate and access gross margins for each client using disparate ERP and CRM functions?

Shorter-Term Contracts

The subscription revenue model has become omnipresent in the business community in the last fifteen years. Companies in numerous industries have widely adopted this business model. There is a subscription offering for shaving razors and luxury watch rentals – so it’s not just applicable to SaaS businesses. Similar to the subscription model, the ensuing dynamic will be shorter-term contracts. Nothing delineates pricing models like a challenging economic environment. It is much harder for businesses to stop paying for a $2,000 monthly enterprise license than to cancel a $25,000 annual subscription.

With the annual subscription model, customers are locked into longer cycles when they may need certain tools for specific projects. A common question customers ask during an economic downturn is if the company has a monthly payment option for their product or service. Even in the event that the business intends to renew services for the entire year, the shorter-term contract offers customers the flexibility to manage their liquidity in uncertain times.

There is some silver lining to these changes. For all the benefits of shorter-term contracts, customers are willing to pay more for the product. Annual contracts can require a hefty upfront cost that requires shorter-term payments. Customers are willing to pay for the agility and flexibility offered by short-term contracts. Furthermore, shorter-term contracts are a great way to showcase all the use cases and benefits of an ERP or any other product. It is an excellent way for companies to get their foot in the door and let the service level win customers over and limit churn.

Integrated Payments

ERPs with integrated payments systems allow customers to check out quickly and process payments that are already on file, securely stored on the ERP. There are multiple benefits to this feature. First, it speeds up the checkout process. The decreased friction in the sales cycle translates into a higher likelihood of closing the transaction. Second, all this manifests into better cash flows for merchants.

Finally, integrated payments can allow merchants to offer customers to pay online and pick up their merchandise from their store locations. Host Merchant Services has a long history of partnering with NetSuite as a third-party payment processing ERP’s API tool CyberSource. HMS easily connects to the integrated platform and manages the end-to-end payment lifecycle, starting from the invoicing process all the way through to payments and reconciliation.

Blockchain

Blockchain has been all the rage lately and is repeatedly touted as the next technology breakthrough that will have a lasting impact on businesses and consumers. Blockchain is distributed and immutable ledger that records transactions and the tracking of both tangible and intangible assets of both companies and individuals.

Blockchain has remarkable potential because it can provide instant access to members of a network permissioned to access all data on the distributed ledger. The blockchain allows customers to access orders placed, payments made, production, inventory, sales, and every other business function, in real-time.

There are practical applications of blockchain for an ERP. For example, Walmart is looking to implement invoice recording, payments, and dispute resolution via the blockchain. Their existing supply chain is already being recorded on the blockchain by linking their delivery fleet’s GPS data to their incoming freight.

Invoicing is another segment of their operation that companies will shift to the blockchain over time. So if there is a dispute related to invoices or the quality of goods received, the blockchain offers immediate insight by accessing the entire digital trail. Still, it can also diagnose the root cause of substandard quality by pinpointing specific production centers. All functions offered by an ERP can easily be shifted onto the blockchain. So, it won’t be long before an ERP is provided solely on the distributed ledger.

Security

There have been a lot of concerns around security, especially for businesses with all the personal and financial data they can access. Plus, the security threats wreak the most havoc with data being compromised, leading to considerable damages resulting from a loss of trust, reputational damage, and most likely lawsuits. One of the best ways for businesses to prepare is to have an ERP with a full scope of security protocols in compliance with the most stringent industry standards.

These standards are a perfect way for merchants to build loyalty among their customers. Numerous brands have clients willing to share their payment details with the likes of Amazon and Apple, given the strong security settings and the use of tokenization to process their transactions, usually in a single click. Customers seldom ever have to reenter their payment information after doing it the first time. It becomes a virtuous loop; customers enter their payment once and never have to do it again. Since they never have to enter their payment details at a particular platform or merchant, they consistently choose to shop on that merchant’s site. This phenomenon of customer loyalty has been greatly documented in a Wharton study on Amazon’s one-click patent and business process[MF1] .

There are numerous SaaS offerings, such as the NetSuite ERP, which is cloud-based and has all the latest security settings, patches, and updates fully implemented and continuously updated as new releases are made automatically. Since the NetSuite ERP also offers integrated payments solutions, the latest payment security standards comply with PCI DSS (Payment Card Industry Data Security Standard). These standards include the Card Code Verification (CVV2), and Address Verification Service (AVS), among many others.

There are many great features that an ERP now offers. It can significantly enhance collaboration and efficiency in businesses that use ERP. Numerous vendors, such as NetSuite, understand the far-reaching impacts robust security protocols have on finance functions and operations. These measures can also enhance customer experience by offering an integrated payments solution.

An ERP is not suitable for all businesses. Even businesses that do deploy an ERP have different needs and use cases that drive their decision-making. The past few years have been essential for merchants as more have started businesses in industries where an ERP can offer tremendous benefits. Furthermore, ERPs themselves have implemented many features and functionalities that are increasingly useful to businesses, including cloud-based SaaS offerings, mobile functionalities, and integrated tools for multiple teams such as Sales, Support, and Marketing to enable enhanced collaboration. As businesses consider their needs for ERPs, it is vital to keep a watchful eye on all the latest trends of 2023.

[MF1]https://knowledge.wharton.upenn.edu/article/amazons-1-click-goes-off-patent/

Banks Use of AI to Manage Credit Risk Tripled In the Last Three Years

Banks are using artificial intelligence or AI more than ever to interact with customers. Banks can use AI to produce chatbots that let banks interact with people at any time. They can also use AI to identify fraud and other potential threats. It can even work for mobile banking purposes, as banks can help customers send money to other accounts based on signals and reports they receive.

One other way banks are using AI involves how they can review customers’ credit risk. Banks are often willing to extend credit to customers, but they need to choose the right people to support. Failing to give support to customers that can afford a bank’s services can lead to defaults and other financial issues.

Credit card delinquencies have increased in the past year. People are also struggling to pay off their loans, especially as they struggle to find stable work. But an AI-powered system can help banks review customer data and identify the potential credit risks they hold. AI can analyze prior user data, transaction reports, and credit histories to see if some people are likely to become insolvent or otherwise unable to pay off their loans or other investments.

AI can also identify fraud risks and ensure they do not occur. AI can check on how customers behave and compare that data with prior fraud reports to spot when someone might be engaging in questionable activities with one’s funds.

The AI effort helps banks find the right people to support. AI increases the bank’s potential to earn revenue without adding to its risk.

AI also reduces the unpredictability surrounding the banking industry. Clients are more unpredictable than ever before. It becomes tough for some people to figure out who is right for lending purposes. AI helps identify unique trends and habits in people, ensuring their behaviors are easier for everyone to predict. It becomes easier to confirm certain things when AI works well.

Managing AI In a Time of Uncertainty

The 2021 calendar year will be a time when the economy gets back up and running and people start to find jobs once again. Government stimulus programs have also helped keep the economy moving. But many banks and other financial institutions are uncertain as to what will happen soon.

The uncertainty surrounding the economy has made banks worried about how they can provide lending services to customers. With this in mind, AI can identify possible concerns surrounding who gets funds through loans.

Handling Data From More Sources

It used to be that banks would have more personal relationships with their clients. Local branches would understand each person’s distinct needs and find banking solutions that fit what they demand. But the banking sector has seen some dramatic changes in the last few years, as data is coming from many sources. People are completing more digital transactions than ever before. Some people even have their funds secured in multiple spaces, including separate spots for their 401ks or IRAs.

AI-based systems can collect data from multiple sources. They can gather data from different service providers, online networks, and even blockchain-based systems. The information helps these banks find details on each client while reducing possible fraud or insolvency risks. Banks can attain more revenue while reducing their costs by using AI to automatically review each customer’s financial profile through many confirmed sources.

Working With Data Mining

Banks with at least $100 billion in assets are more likely to utilize AI to review risky customers. But AI use has become common among smaller banks as well. Part of this comes from how AI works alongside data mining processes. Data mining has been in use in the banking industry for a while now, as it helps identify unusual patterns and shifts in large data sets. The mining effort helps banks review ways they can increase their revenues and reduce costs.

AI systems can incorporate data mining in their processes to help them stay functional. It can review massive data sets used in the data mining function and incorporate the mining results into its research database. The AI can then use those details to identify possible threats and opportunities surrounding people who want to borrow funds from the bank.

What People Use AI For Today

Banks are using AI to manage many risk mitigation efforts. Some of the things that AI is being used for include:

Identifying discrepancies in data entries, especially for new accounts or files
Helping to make credit decisions for applicants
Underwriting for credit risks
Finding solutions to possible credit problems clients may hold

The AI can work with data mining results and prior reports to see what can work. AI makes it easier for banks to ensure these systems work well.

Interacting With Customers

AI can also interact with customers who want to apply for banking services. AI systems can reach these customers through multiple processes:

An AI system can provide quick answers on a website based on a customer’s behavior. The AI could review one’s online actions and provide responses to search queries and other actions.
Chat-driven communications may also work. Chatbots are prominent AI examples for how they can read language notes and identify demands for info.
Customers can also enter emails that illustrate their concerns. An AI system can produce an automated response based on unique keywords someone enters, the tone of the message, and other points surrounding the writer’s needs. The work ensures the customer will get the answer one requests sooner.

Artificial intelligence is necessary for helping banks find the right people to support for investment purposes. AI will do well for many investment purposes, making it a suitable solution for everyone to follow. People will continue to express various risks for banks to review, so it is essential to watch for what might happen.

Improving the Bottom Line With Fraud Mitigation

Ecommerce fraud has become a significant concern in today’s economy. People are flocking online more than ever before to make purchases. Some retailers are also focusing more on their digital commerce efforts than their in-store work.

People are using digital commerce services more than ever, but there are worries about the fraud mitigation efforts these companies use. Some businesses are unaware of what they can do to stay safe while online. Others might not be willing to evolve their websites to make them more secure and functional.

But more people are engaging in ecommerce fraud than ever before, as businesses lost about $17.5 billion in online fraud this past year. That total is expected to rise to $20 billion in 2021, especially as people become more reliant on digital sales and less on going to traditional outlets for things.

Many of these losses come from synthetic ID fraud. The practice entails a user using another person’s identifiable data to acquire something online. The person who makes a transaction is not the person that the website assumes is making the deal.

New efforts to mitigate the risks of online fraud are critical for the industry’s survival. The threat of synthetic ID fraud is too significant for people to ignore, as are various other worries. But artificial intelligence can be critical to preventing possible threats from becoming worse.

Fraud Mitigation – Synthetic ID Fraud Concerns

The most significant worry about synthetic ID fraud is that it isn’t easy for traditional fraud mitigation measures to identify. Sometimes synthetic fraud entails using one piece of identifiable data to move forward. A person’s Social Security Number could work, but the person’s address or name may not be there. A website could assume the customer is the one that links to the SSN in this example.

Sometimes the synthetic fraud will entail behaviors that are similar to what someone might utilize online. These issues are impossible for some old online platforms to recognize. It becomes easier for people to get away with fraud this way, forcing businesses to write off their losses.

Other Fraudulent Activities

Online fraud can occur on any shopping website through many other methods:

A person might steal credit card data and test it on a website. The person can test the card to see the possible credit limit on that card. Once someone knows that a card works, that person will want to continue making expensive transactions on that card.
People could steal passwords and other bits of verification data when getting online. A person might use the data one finds to impersonate an actual person’s account.
Interception fraud can occur when someone uses the same billing and shipping info on a stolen card, but the person will intercept the goods in transit. The customer might contact a customer service department to change the shipping address right before moving out of a warehouse.

Many other fraud instances could occur, and they can all be dramatic. The worries that people have surrounding fraud can be dangerous and risky, but they don’t have to be worrisome if the best measures work. Artificial intelligence is a suitable solution to use, as the next section shows.

AI Is Necessary

Artificial intelligence-based solutions will be critical for helping businesses stay safe and to avoid fraud. AI can review customer actions and compare them with general signs of fraud. For example, an AI system can flag situations where someone tries to commit interception fraud by changing the shipping address after placing the order.

An AI system can use a database that highlights general examples of fraud and common warning signs. The AI review will compare multiple activities in a transaction with the known fraud instances and then flag transactions that may be a concern.

Depending on the setup a business uses, the company can either alert a customer or block the transaction altogether. The held transaction could also be secured if the customer provides enough data to confirm one’s identity. The work can be extensive at times, but it is about ensuring everything happening online stays safe and secure without risking possible losses on either end of the deal.

There are many ways how an AI system can work:

Customer behaviors can be gauged versus what people normally do on a website. A website can review when someone gets online, when that person is purchasing things, and where someone accesses a website.
A system can also review the payment methods that people use. An entity that uses multiple payment methods might be trying to use many accounts for the same item.
Some parties may be using foreign sources for funds. They might use credit cards issued by banks in different countries. Others might be using funds through accounts that support cryptocurrencies that some retailers might not accept for payment purposes.

A business can use multiple third-party programs to identify connection sources and to verify addresses and other details. The business can include these programs surrounding whatever one feels is right for use.

The goal of the analysis is to reduce the risk of chargebacks by identifying fraudulent cases as soon as possible. All activities can be reviewed versus whatever norms the website experiences.

Responding Is Critical

All online retailers must be ready to respond to potential fraud cases. The process requires twenty-four-hour support that can identify anything new.

But the response should include a personal touch. A company must review the norms that customers express and find cases where something is outside the ordinary. It becomes easier for businesses to reduce their fraud risks when they recognize what is working and what they should be doing when keeping their efforts afloat.

Fraud is a significant worry that can impact any business, but it will be easier to rebound and reduce risks if the right measures work. Businesses can stop various concerns if they know what they are doing while recognizing possible changes that might occur after a while.

MasterCard Using Artificial Intelligence to Attack False Declines